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Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study

Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study
Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study

Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r 2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention.

1549-1277
Forgetta, Vincenzo
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Keller-Baruch, Julyan
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Forest, Marie
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Durand, Audrey
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Bhatnagar, Sahir
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Kemp, John P.
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Nethander, Maria
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Evans, Daniel
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Morris, John A.
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Kiel, Douglas P.
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Rivadeneira, Fernando
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Johansson, Helena
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Harvey, Nicholas
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Mellström, Dan
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Karlsson, Magnus
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Cooper, Cyrus
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Evans, David M.
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Clarke, Robert
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Kanis, John A.
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Orwoll, Eric
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McCloskey, Eugene
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Ohlsson, Claes
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Pineau, Joelle
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Leslie, William D.
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Greenwood, Celia M.T.
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Richards, J. Brent
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Forgetta, Vincenzo
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Forest, Marie
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Durand, Audrey
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Bhatnagar, Sahir
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Kemp, John P.
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Nethander, Maria
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Evans, Daniel
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Morris, John A.
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Harvey, Nicholas
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Mellström, Dan
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Karlsson, Magnus
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Cooper, Cyrus
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Evans, David M.
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Clarke, Robert
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Kanis, John A.
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Orwoll, Eric
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Ohlsson, Claes
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Pineau, Joelle
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Leslie, William D.
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Greenwood, Celia M.T.
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Richards, J. Brent
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Forgetta, Vincenzo, Keller-Baruch, Julyan, Forest, Marie, Durand, Audrey, Bhatnagar, Sahir, Kemp, John P., Nethander, Maria, Evans, Daniel, Morris, John A., Kiel, Douglas P., Rivadeneira, Fernando, Johansson, Helena, Harvey, Nicholas, Mellström, Dan, Karlsson, Magnus, Cooper, Cyrus, Evans, David M., Clarke, Robert, Kanis, John A., Orwoll, Eric, McCloskey, Eugene, Ohlsson, Claes, Pineau, Joelle, Leslie, William D., Greenwood, Celia M.T. and Richards, J. Brent (2020) Development of a polygenic risk score to improve screening for fracture risk: A genetic risk prediction study. PLoS Medicine, 17 (7), [e1003152]. (doi:10.1371/journal.pmed.1003152).

Record type: Article

Abstract

Background Since screening programs identify only a small proportion of the population as eligible for an intervention, genomic prediction of heritable risk factors could decrease the number needing to be screened by removing individuals at low genetic risk. We therefore tested whether a polygenic risk score for heel quantitative ultrasound speed of sound (SOS)—a heritable risk factor for osteoporotic fracture—can identify low-risk individuals who can safely be excluded from a fracture risk screening program. Methods and findings A polygenic risk score for SOS was trained and selected in 2 separate subsets of UK Biobank (comprising 341,449 and 5,335 individuals). The top-performing prediction model was termed “gSOS”, and its utility in fracture risk screening was tested in 5 validation cohorts using the National Osteoporosis Guideline Group clinical guidelines (N = 10,522 eligible participants). All individuals were genome-wide genotyped and had measured fracture risk factors. Across the 5 cohorts, the average age ranged from 57 to 75 years, and 54% of studied individuals were women. The main outcomes were the sensitivity and specificity to correctly identify individuals requiring treatment with and without genetic prescreening. The reference standard was a bone mineral density (BMD)–based Fracture Risk Assessment Tool (FRAX) score. The secondary outcomes were the proportions of the screened population requiring clinical-risk-factor-based FRAX (CRF-FRAX) screening and BMD-based FRAX (BMD-FRAX) screening. gSOS was strongly correlated with measured SOS (r 2 = 23.2%, 95% CI 22.7% to 23.7%). Without genetic prescreening, guideline recommendations achieved a sensitivity and specificity for correct treatment assignment of 99.6% and 97.1%, respectively, in the validation cohorts. However, 81% of the population required CRF-FRAX tests, and 37% required BMD-FRAX tests to achieve this accuracy. Using gSOS in prescreening and limiting further assessment to those with a low gSOS resulted in small changes to the sensitivity and specificity (93.4% and 98.5%, respectively), but the proportions of individuals requiring CRF-FRAX tests and BMD-FRAX tests were reduced by 37% and 41%, respectively. Study limitations include a reliance on cohorts of predominantly European ethnicity and use of a proxy of fracture risk. Conclusions Our results suggest that the use of a polygenic risk score in fracture risk screening could decrease the number of individuals requiring screening tests, including BMD measurement, while maintaining a high sensitivity and specificity to identify individuals who should be recommended an intervention.

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Accepted/In Press date: 3 June 2020
e-pub ahead of print date: 2 July 2020
Published date: 2 July 2020

Identifiers

Local EPrints ID: 445548
URI: http://eprints.soton.ac.uk/id/eprint/445548
ISSN: 1549-1277
PURE UUID: 73c3a53c-8e1b-4ac9-9522-37d0b6779e2e
ORCID for Nicholas Harvey: ORCID iD orcid.org/0000-0002-8194-2512
ORCID for Cyrus Cooper: ORCID iD orcid.org/0000-0003-3510-0709

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Date deposited: 15 Dec 2020 17:31
Last modified: 06 Jun 2024 01:42

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Contributors

Author: Vincenzo Forgetta
Author: Julyan Keller-Baruch
Author: Marie Forest
Author: Audrey Durand
Author: Sahir Bhatnagar
Author: John P. Kemp
Author: Maria Nethander
Author: Daniel Evans
Author: John A. Morris
Author: Douglas P. Kiel
Author: Fernando Rivadeneira
Author: Helena Johansson
Author: Nicholas Harvey ORCID iD
Author: Dan Mellström
Author: Magnus Karlsson
Author: Cyrus Cooper ORCID iD
Author: David M. Evans
Author: Robert Clarke
Author: John A. Kanis
Author: Eric Orwoll
Author: Eugene McCloskey
Author: Claes Ohlsson
Author: Joelle Pineau
Author: William D. Leslie
Author: Celia M.T. Greenwood
Author: J. Brent Richards

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